SOTAVerified

DeepFake Detection

DeepFake Detection is the task of detecting fake videos or images that have been generated using deep learning techniques. Deepfakes are created by using machine learning algorithms to manipulate or replace parts of an original video or image, such as the face of a person. The goal of deepfake detection is to identify such manipulations and distinguish them from real videos or images.

Description source: DeepFakes: a New Threat to Face Recognition? Assessment and Detection

Image source: DeepFakes: a New Threat to Face Recognition? Assessment and Detection

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 301–325 of 580 papers

TitleStatusHype
Big Brother is Watching: Proactive Deepfake Detection via Learnable Hidden Face—0
BiHPF: Bilateral High-Pass Filters for Robust Deepfake Detection—0
CAD: A General Multimodal Framework for Video Deepfake Detection via Cross-Modal Alignment and Distillation—0
Can deepfakes be created by novice users?—0
Can Multi-modal (reasoning) LLMs work as deepfake detectors?—0
Capture Artifacts via Progressive Disentangling and Purifying Blended Identities for Deepfake Detection—0
Classifying Deepfakes Using Swin Transformers—0
Codecfake: An Initial Dataset for Detecting LLM-based Deepfake Audio—0
Comparative Analysis of Deep Convolutional Neural Networks for Detecting Medical Image Deepfakes—0
Comparative Analysis of Deep-Fake Algorithms—0
Comparative Analysis of Deepfake Detection Models: New Approaches and Perspectives—0
Complex-valued neural networks for voice anti-spoofing—0
Context-aware TFL: A Universal Context-aware Contrastive Learning Framework for Temporal Forgery Localization—0
Continuous fake media detection: adapting deepfake detectors to new generative techniques—0
Contrastive Learning for DeepFake Classification and Localization via Multi-Label Ranking—0
Contrastive Learning of Global and Local Video Representations—0
Contrastive Self-Supervised Learning of Global-Local Audio-Visual Representations—0
Cost Sensitive Optimization of Deepfake Detector—0
Cross-Branch Orthogonality for Improved Generalization in Face Deepfake Detection—0
Cross-Domain Audio Deepfake Detection: Dataset and Analysis—0
Cross-Domain Local Characteristic Enhanced Deepfake Video Detection—0
Datasets, Clues and State-of-the-Arts for Multimedia Forensics: An Extensive Review—0
DDL: A Dataset for Interpretable Deepfake Detection and Localization in Real-World Scenarios—0
DeePen: Penetration Testing for Audio Deepfake Detection—0
Deepfake Audio Detection Using Spectrogram-based Feature and Ensemble of Deep Learning Models—0
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All datasetsFakeAVCelebFaceForensicsDFDC1CIFAKE: Real and AI-Generated Synthetic ImagesCOCOFakeDFFDLAV-DF

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1AV-Lip-Sync+Accuracy (%)99.29—Unverified
2AvtenetAccuracy (%)98.57—Unverified
3FACTORROC AUC97.4—Unverified
4RealForensicsROC AUC97.1—Unverified
5AVADROC AUC94.5—Unverified
6AV-Lip-Sync ModelAccuracy (%)94—Unverified
7FTCNROC AUC93.1—Unverified
8LipForensicsROC AUC91.1—Unverified
9Multimodal Ensemble ModelAccuracy (%)89—Unverified
10AD DFDROC AUC88.1—Unverified
#ModelMetricClaimedVerifiedStatus
1XceptionNetDF96.36—Unverified
2QAD-EAUC0.96—Unverified
3EfficientNetB4 + EfficientNetB4ST + B4Att + B4AttSTAUC0.94—Unverified
4MARLIN (ViT-L)AUC0.94—Unverified
5MARLIN (ViT-B)AUC0.93—Unverified
6MARLIN (ViT-S)AUC0.89—Unverified
7EfficientNetB4 + EfficientNetB4ST + B4AttSTLogLoss0.33—Unverified
#ModelMetricClaimedVerifiedStatus
1Cross Efficient Vision TransformerAUC0.95—Unverified
2Efficient Vision TransformerAUC0.92—Unverified
3EfficientNetB4 + EfficientNetB4ST + B4AttLogLoss0.46—Unverified
#ModelMetricClaimedVerifiedStatus
1STYLE0L99—Unverified
#ModelMetricClaimedVerifiedStatus
1FasterThanLiesAUC99.65—Unverified
#ModelMetricClaimedVerifiedStatus
1FasterThanLiesAUC1—Unverified
#ModelMetricClaimedVerifiedStatus
1FasterThanLiesAUC1—Unverified
#ModelMetricClaimedVerifiedStatus
1BA-TFDAUC0.99—Unverified